Official Implementation of the Bi-KVIL paper
BibTeX:
@ARTICLE {gao_kvil_2023,
author = {Jianfeng Gao and Zhi Tao and Noémie Jaquier and Tamim Asfour},
title = {K-VIL: Keypoints-based Visual Imitation Learning},
pages = {3888--3908},
volume ={39},
number ={5},
journal ={IEEE Transactions on Robotics},
year = {2023}
}
@INPROCEEDINGS {gao_bikvil_2024,
author = {Jianfeng Gao and Xiaoshu Jin and Franziska Krebs and Noémie Jaquier and Tamim Asfour},
title = {Bi-KVIL: Keypoints-based Visual Imitation Learning of Bimanual Manipulation Tasks},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
year = {2024}
}
If conda is not yet available on your computer,
install Miniconda, e.g., for python 3.10.
To run the downloaded script, you may need to enable its execution using chmod u+x ~/Downloads/Miniconda[...].sh
.
After the installation, you can disable the auto-activation of the default "base" environment, as described in the installer output.
Get and run the installation script for kvil. If you modify the paths, be aware to either add or leave out the concluding slash (/
) dependent on how the default path is defined.
wget https://raw.githubusercontent.com/wyngjf/bi-kvil-pub/main/scripts/kvil_install.sh
source kvil_install.sh
After installation, run
robot_vision_install
and select (up / down arrow to navigate and space to select or deselect) the following dependencies.
- apex
- graphormer
- groundingdino
- mmpose
- opendr
- raft
- sam
- aot
- unimatch
Pay attention to the terminals. If you don't have CUDA configured properly, you may encounter problems when installing
groundingDINO
. The script will just continue with error. You need to solve those issues accordingly and run the command again.
see tutorial on Recording